Title :
A novel prediction method for body fat by using Choquet integral with respect to L-measure and Gamma-support
Author :
Chen, I-ju ; Lee, Ming-jung ; Jeng, Bai-cheng ; Wu, Der-Bang
Author_Institution :
Dept. of Phys. Educ., Asia Univ., Wufeng, Taiwan
Abstract :
Establishing a good algorithm for predicting body fat of body composition is an important issue. In this study, a novel body fat prediction method by using Choquet integral regression model based on L-measure and Gamma-support is proposed. For evaluating the performance of this new algorithm, a 5-fold Cross-Validation RMSE is performed. Experimental result shows that this new prediction scheme is better than the Choquet integral regression model based on Gamma-measure and P-measure, respectively and two traditional prediction models, ridge regression and multiple regression models, respectively.
Keywords :
integral equations; regression analysis; 5-fold cross-validation RMSE; Choquet integral regression model; Gamma-support; L-measure; body composition; body fat prediction; multiple regression model; performance evaluation; prediction method; ridge regression; Asia; Biological system modeling; Cybernetics; Fuzzy sets; Linear regression; Machine learning; Performance evaluation; Prediction methods; Predictive models; Vectors;
Conference_Titel :
Machine Learning and Cybernetics, 2009 International Conference on
Conference_Location :
Baoding
Print_ISBN :
978-1-4244-3702-3
Electronic_ISBN :
978-1-4244-3703-0
DOI :
10.1109/ICMLC.2009.5212802